Abstract
The analog design assistance tool Adapt [5, 6] has been developed to help analog electronic circuit designers tuning design parameters, such that the functional design specifications are met, given process technology constraints. Tuning is based on an optimization process, in which each iteration of the optimization loop implies the evaluation of the circuit by an analog circuit simulator. Considering the simulator as a black box tool, the choice of the optimization technique is restricted, because the simulator does not automatically supply derivatives of the design metrics and numerical noise is inherently present (for instance due to adaptive time stepping). Therefore, optimization algorithms that adopt finite-difference schemes to approximate derivatives cannot be applied straightforwardly.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bazaraa, M.S., Sherali, H.D., Shetty, C.M.: Nonlinear programming: theory and algorithms, 2nd edition. John Wiley and Sons, New York (1993)
Conn, A.R., Gould, N., Toint, Ph.L.: Global convergence of a class of trust region algorithms for optimization with simple bounds. SIAM J. Numer. Anal., 25, 433460 (1988)
Elster, C., Neumaier, A.: A grid algorithm for bound constrained optimization of noisy functions. IMA J. Numer. Anal., 15, 585–608 (1995)
Fang, K.-T., Wang, Y.: Number-theoretic methods in statistics. Chapman and Hall, London (1994)
Kole, M., Heijmen, T., Kevenaar, T., Pranger, H.-J., Sevat, M.: Adapt, an interactive tool for analog synthesis. In: Proc. SAME-2001 Conf., Sophia Antipolis, France, 15–19 (2001)
Lin, C., Heijmen, T., ter Maten, J., Kole, M.: ADAPT: Design assistance for iterative analog synthesis. In: Analog 2002 — Entwicklung von Analogschaltungen mit CAE-Methoden. GMM-Fachbericht 38, VDE Verlag GMBH, Berlin, 195–200 (2002)
Nelder, J.A., Mead, R.: A simplex method for function minimization. The Computer Journal, 7–4, 308–313 (1965)
Rodriguez, J.F., Renaud, J.E., Watson, L.T.: Convergence of trust region augmented Lagrangian methods using variable fidelity approximation data. Structural Optim., 15, 141–156 (1998)
Wright, M.H.: Direct search methods: once scorned, now respectable. In: Griffiths, D.F., Watson, G.A. (eds) Numerical analysis 1995. Addison—Wesley Longman, Harlow, 191–208 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Heijmen, T.G.A., Lin, C., ter Maten, E.J.W., Sevat, M.F. (2004). Augmented Lagrangian Algorithm for Optimizing Analog Circuit Design. In: Buikis, A., Čiegis, R., Fitt, A.D. (eds) Progress in Industrial Mathematics at ECMI 2002. The European Consortium for Mathematics in Industry, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-09510-2_21
Download citation
DOI: https://doi.org/10.1007/978-3-662-09510-2_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07262-8
Online ISBN: 978-3-662-09510-2
eBook Packages: Springer Book Archive